Extending Goodman-Kruskal's gamma to the comparison of ordered treatments in multicenter clinical trials.

In a randomized, multicenter clinical trial setting, the treatments may consist of increasing doses of a drug and placebo and the response variable may be ordinal (e.g., physician's global evaluation of treatment effectiveness). Within each center (e.g., hospital), patients are randomly assigned to treatments (rows) such that the row totals are fixed and the rows form a product-multinomial sample of the ordinal response variable. Gamma, a measure of ordinal association in two-way contingency tables, and its asymptotic standard error can be estimated from the data in each center. We use these independent estimates of gamma for testing the hypothesis of homogeneity of gammas, controlling for center effect. If this hypothesis is not rejected, the within-center estimates of gamma can be combined to form a common gamma across the centers.     

Design and analysis of trials with quality of life as an outcome: a practical guide.

Health Related Quality of Life (HRQoL) measures are becoming more frequently used in clinical trials, as both primary and secondary endpoints. Investigators are now asking statisticians for advice on how to plan (e.g., sample size) and analyze studies using HRQoL measures. HRQoL measures such as the SF-36 are usually measured on an ordered categorical (ordinal) scale. In the designing stages and when analyzing, the scales are often scored and the scores treated as if they were continuous and normally distributed. However the ordinal scaling of HRQoL measures leads to problems in determining sample size, and conventional parametric methods of estimation and hypothesis testing may not be appropriate for such outcomes. We present practical guidelines for the design and analysis of trials with HRQoL measures as outcomes. We used conventional statistical methods (i.e., t-tests and multiple regression), various ordinal regression models (proportional odds, continuation ratio, polytomous and stereotype) and bootstrap methods to analyze an HRQoL dataset. To illustrate the various methods we used HRQoL data on the SF-36 Role Limitations Emotional dimension for two groups of patients with leg ulcers. The bootstrap, t-test, and multiple regression methods gave similar results. The various ordinal regression models also gave similar results. If the HRQoL measure has a large number of ordered categories, most of which are occupied, and the underlying scale really is continuous but measured imperfectly by an instrument with a limited number of discrete values, then an informal rule of thumb is that this discrete scale should be treated as continuous if it has seven or more categories and as ordinal otherwise.     

Stratified Multivariate Mann–Whitney Estimators for the Comparison of Two Treatments with Randomization Based Covariance Adjustment

Methodology for comparing two randomly assigned treatments for strictly ordinal response variables has been discussed throughout the literature on multivariate Mann–Whitney estimators with stratification adjustment. Although such estimators can be computed directly as weighted linear combinations of within-stratum Mann–Whitney estimators, consistent estimation of their covariance matrix is done using methods for multivariate U-statistics. The scope of these methods includes ways of managing randomly missing data and ways to invoke randomization-based covariance adjustment for no differences between treatments for background or baseline covariables. The assessment of treatment differences can be done using confidence intervals or statistical tests for the adjusted Mann–Whitney estimators. The methods in this article are illustrated using three examples. The first example is a randomized clinical trial with eight strata and a univariate ordinal response variable. The second example is a randomized clinical trial with four strata, two covariables, and four ordinal response variables. The third example is a randomized two-period crossover clinical trial with four strata, three covariables (as age, screening, first baseline), three response variables (as first period response, second baseline, second period response), and missing data. For these examples, the results are interpretable through the probability of better outcomes for one treatment over the other.     

Pair differences-U-test. A distribution-free comparative study of two therapies]

Distribution-free comparison of the effects of two therapies The Wilcoxon-Mann-Whitney test forms the basis for the following common test-problem according to which the U-test should be performed. On two rows of independent -- connected in parallell -- matched paired samples a continuous variable is determined. Observations on a single pair are contributed to the identical individuum. The question that arises is formulated as follows. Can the differences of a pair of the two rows of samples -- connect in parallel -- be distinguished from each other with regard to their location? To answer this question a modified application of the U-test is proposed. This test can be used to compare the efficacy of two different treatments. Other uses of this test are also possible.     

DESIGN AND ANALYSIS OF TRIALS WITH QUALITY OF LIFE AS AN OUTCOME: A PRACTICAL GUIDE

Health Related Quality of Life (HRQoL) measures are becoming more frequently used in clinical trials, as both primary and secondary endpoints. Investigators are now asking statisticians for advice on how to plan (e.g., sample size) and analyze studies using HRQoL measures.

HRQoL measures such as the SF-36 are usually measured on an ordered categorical (ordinal) scale. In the designing stages and when analyzing, the scales are often scored and the scores treated as if they were continuous and normally distributed. However the ordinal scaling of HRQoL measures leads to problems in determining sample size, and conventional parametric methods of estimation and hypothesis testing may not be appropriate for such outcomes.

We present practical guidelines for the design and analysis of trials with HRQoL measures as outcomes.

We used conventional statistical methods (i.e., t-tests and multiple regression), various ordinal regression models (proportional odds, continuation ratio, polytomous and stereotype) and bootstrap methods to analyze an HRQoL dataset. To illustrate the various methods we used HRQoL data on the SF-36 Role Limitations Emotional dimension for two groups of patients with leg ulcers.

The bootstrap, t-test, and multiple regression methods gave similar results. The various ordinal regression models also gave similar results.

If the HRQoL measure has a large number of ordered categories, most of which are occupied, and the underlying scale really is continuous but measured imperfectly by an instrument with a limited number of discrete values, then an informal rule of thumb is that this discrete scale should be treated as continuous if it has seven or more categories and as ordinal otherwise.     

Central cholinergic involvement in behavioral hyper-reactivity.

The present experiments were designed to test the hypothesis that behavioral reactivity to changes of environmental stimulation varies concomitantly with changes induced acutely by pharmacological and chronically by morphological manipulations of acetylcholine in the central cholinergic system. Acute reduction of acetylcholine levels was achieved by cerebroventricular injections of hemicholinium-3 at five dosages and chronic reduction by electrolytic lesions in the septum. Significant and quantitatively equivalent hyper-reactivity occurred when animals were exposed to a variety of stimulus changes at peak effect times for the two experimental treatments. Such concordance of behavioral effects was not observed during non-contingent shock stimulation, when septal animals were significantly hyper-reactive and hemicholinium-3 animals were not. These findings may be interpreted in terms of results of recent multivariate analyses showing that several independent behavioral factors constitute the septal “syndrome”: a particular factor, e.g., reactivity, may be related to a neurochemical substrate which is not shared by other factors. The present experiments revealed a highly precise relation between acute changes in acetylcholine levels and dose effect trends in hyper-reactivity, i.e., hyper-reactivity followed hemicholinium-3 injections (IVt) which reduced acetylcholine and returned to control levels when acetylcholine recovered. Under conditions of chronic acetylcholine reduction (septal lesion) initial hyper-reactivity disappeared with time, an observation consistent with the “imbalance” hypothesis about interactions between transmitter systems which assumes that changes in one system may be followed by compensatory changes in a related system.     

Interspecies scaling,allometry, physiological time,and the ground plan of pharmacokinetics

Interspecies variation in pharmacokinetics is considered and treated as a property and consequence of body size (allometry). Consequently, it is possible to reference (scale) pharmacokinetic parameters to the organism's individual anatomy, biochemistry, and/or physiology in such a manner that differences between species are nullified. Thus, in the mouse, rat, dog, monkey, and human, methotrexate plasma clearance always equals 133% of creatinine clearance and as such becomes invariant. Pharmacokinetic time (a variable in terms of chronological time) is shown to be a form of physiological time in which a pharmacokinetic event becomes the independent variable, e.g., disposition halflife. A relationship between pharmacokinetic time and body size is demonstrated. It is suggested that man's lesser quantitative ability to metabolize many drugs may be correlated with his enhanced longevity.     

Environmental Distribution,Analysis, and Toxicity of Organometal(loid) Compounds

ABSTRACT

The biochemical modification of the metals and metalloids mercury, tin, arsenic, antimony, bismuth, selenium, and tellurium via formation of volatile metal hydrides and alkylated species (volatile and involatile) performs a fundamental role in determining the environmental processing of these elements. In most instances, the formation of such species increases the environmental mobility of the element, and can result in bioaccumulation in lipophilic environments. While inorganic forms of most of these compounds are well characterized (e.g., arsenic, mercury) and some of them exhibit low toxicity (e.g., tin, bismuth), the more lipid-soluble organometals can be highly toxic. Methylmercury poisoning (e.g., Minamata disease) and tumor development in rats after exposure to dimethylarsinic acid or tributyltin oxide are just some examples. Data on the genotoxicity (and the neurotoxicity) as well as the mechanisms of cellular action of organometal(loid) compounds are, however, scarce. Many studies have shown that the production of such organometal(loid) species is possible and likely whenever anaerobic conditions (at least on a microscale) are combined with available metal(loid)s and methyl donors in the presence of suitable organisms. Such anaerobic conditions can exist within natural environments (e.g., wetlands, pond sediments) as well as within anthropogenic environmental systems (e.g., waste disposal sites and sewage treatments plants). Some methylation can also take place under aerobic conditions. This article gives an overview about the environmental distribution of organometal(loid) compounds and the potential hazardous effects on animal and human health. Genotoxic effects in vivo and in vitro in particular are discussed.     

Managing psychiatric disorders with antidiabetic agents: translational research and treatment opportunities

The objective of this paper is to synthesise extant studies describing the neurotherapeutic effects of antidiabetic agents in neuropsychiatric disorders. The authors conducted a MedLine search of all English-language articles published between 1966 and March 2006. The search terms were the nonproprietary names of established and putative antidiabetic agents (e.g., insulin, insulin secretagogues and sensitisers) cross-referenced with the individual names of Diagnostic and Statistical Manual of Mental Disorders (DSM)-III-R/IV/-TR-defined mood, psychotic, anxiety and dementing disorders. The search was augmented with a manual review of article reference lists. Contemporary models of disease pathophysiology in major depressive disorder, bipolar disorder and several dementing disorders (e.g., Alzheimer’s disease) emphasise alterations in cellular plasticity and cytoarchitecture, with associated regional abnormalities in neuronal and glial density and morphology. Antidiabetic treatments (e.g., thiazolidinediones) may be capable of attenuating this pathological process via disparate mechanisms (e.g., neuroprotective, neurotrophic, anti-inflammatory). Enhanced insulin signalling with antidiabetic treatments may preserve and/or augment cognitive function in several neuropsychiatric disorders. Antidiabetic treatments, which maintain euglycaemia, hold promise as potent and clinically significant therapeutic interventions for several neuropsychiatric disorders.     

Environmental distribution, analysis, and toxicity of organometal(loid) compounds

The biochemical modification of the metals and metalloids mercury, tin, arsenic, antimony, bismuth, selenium, and tellurium via formation of volatile metal hydrides and alkylated species (volatile and involatile) performs a fundamental role in determining the environmental processing of these elements. In most instances, the formation of such species increases the environmental mobility of the element, and can result in bioaccumulation in lipophilic environments. While inorganic forms of most of these compounds are well characterized (e.g., arsenic, mercury) and some of them exhibit low toxicity (e.g., tin, bismuth), the more lipid-soluble organometals can be highly toxic. Methylmercury poisoning (e.g., Minamata disease) and tumor development in rats after exposure to dimethylarsinic acid or tributyltin oxide are just some examples. Data on the genotoxicity (and the neurotoxicity) as well as the mechanisms of cellular action of organometal(loid) compounds are, however, scarce. Many studies have shown that the production of such organometal(loid) species is possible and likely whenever anaerobic conditions (at least on a microscale) are combined with available metal(loid)s and methyl donors in the presence of suitable organisms. Such anaerobic conditions can exist within natural environments (e.g., wetlands, pond sediments) as well as within anthropogenic environmental systems (e.g., waste disposal sites and sewage treatments plants). Some methylation can also take place under aerobic conditions. This article gives an overview about the environmental distribution of organometal(loid) compounds and the potential hazardous effects on animal and human health. Genotoxic effects in vivo and in vitro in particular are discussed.     

Statistical Methods to Analyze Adverse Events Data of Randomized Clinical Trials

The adverse events data of randomized clinical trials are often analyzed based on either crude incidence rates or exposure-adjusted incidence rates. These rates do not adequately account for an individual patient's profile of adverse events over the study period when an individual may remain in the trial after experiencing one or more events (i.e., occurrence of multiple events of the same kind or different kinds). Moreover, the required statistical assumptions (e.g., constant hazard rate over time) for valid estimates of incidence rates are not likely to be met in practice by adverse events data of clinical trials. A nonparametric approach called the mean cumulative function (MCF) provides a valid statistical inference on recurrent adverse event profiles of drugs in randomized clinical trials. The estimate involves no assumptions about the form of MCF. To demonstrate the applicability and utility of the MCF approach in clinical trial datasets, an adverse event dataset obtained from a clinical trial is analyzed in this article. As compared to the crude or exposure-adjusted incidence rates of adverse events, the MCF estimates facilitate more understanding of safety profiles of a drug in a randomized clinical trial.     

临床试验中中心效应的评价及处理方法

探讨多中心临床试验中，中心效应的评价与处理方法，采用Breslow-Day检验对有效率的中心间差异进行评价，采用CMH方法对组间有效率及疗效等级进行分析，采用logistic回归方法对中心效应及有效率或疗效等级同时进行评价。结果提示，Breslow-Day检验只能对有效率的中心间差异进行评价。而不能对疗效等级的中心差异进行评价，CMH方法不能同时考虑其它协变量的影响。     

Platelet activation, inflammatory mediators and hypercholesterolemia

Atherogenic cofactors, such as altered cholesterol metabolism, may impact locally on inflammatory responses in atherosclerotic lesions. Blood levels of inflammatory markers (e.g., C-reactive protein, fibrinogen) have been associated with hypercholesterolemia and with overt atherothrombotic disorders. More recently. cytokines (e.g., interleukin-6, interleukin-1beta) and soluble adhesion molecules (e.g., selectins, intercellular adhesion molecule-1, vascular cell adhesion molecule-1) have been associated with both hypercholesterolemia and atherosclerotic disease, suggesting their use as potential therapeutic targets for the non-specific "anti-inflammatory" treatment of atherosclerosis. The inflammatory response associated with hypercholesterolemia involves not only the intrinsic cells of the artery wall. but also circulating cells. Platelets participate in this disease process through the release of a wide variety of biologically active substances. An imbalance of the hemostatic system and persistent in vivo platelet activation can be observed in hypercholesterolemia and may have pathophysiological implications in the development and progression of atherosclerotic plaques. Recent findings on the inflammatory actions of platelets have established the potential for a previously unrecognized biologic role for platelets in inflammation and vascular injury, and have opened new perspectives in the comprehension of the pathogenetic mechanism(s) of atherosclerosis. Stimulated platelets actively synthesize proinflammatory cytokines (e.g., CD40L, IL-1beta) and are able to release chemokines (i.e., platelet factor-4, RANTES) which have been all involved in the inflammatory process associated with hypercholesterolemia. This review will summarize the present understanding of the interplay between hypercholesterolemia, inflammation and platelet activation in the development and progression of atherosclerosis, and we also discuss the effects of lipid-lowering treatment on these phenomena.     

Mutagenicity in drug development: interpretation and significance of test results

The use of mutagenicity data has been proposed and widely accepted as a relatively fast and inexpensive means of predicting long-term risk to man (i.e., cancer in somatic cells, heritable mutations in germ cells). This view is based on the universal nature of the genetic material, the somatic mutation model of carcinogenesis, and a number of studies showing correlations between mutagenicity and carcinogenicity. An uncritical acceptance of this approach by some regulatory and industrial concerns is over-conservative, naive, and scientifically unjustifiable on a number of grounds: Human cancers are largely life-style related (e.g., cigarettes, diet, tanning). Mutagens (both natural and man-made) are far more prevalent in the environment than was originally assumed (e.g., the natural bases and nucleosides, protein pyrolysates, fluorescent lights, typewriter ribbon, red wine, diesel fuel exhausts, viruses, our own leukocytes). "False-positive" (relative to carcinogenicity) and "false-negative" mutagenicity results occur, often with rational explanations (e.g., high threshold, inappropriate metabolism, inadequate genetic endpoint), and thereby confound any straightforward interpretation of mutagenicity test results. Test battery composition affects both the proper identification of mutagens and, in many instances, the ability to make preliminary risk assessments. In vitro mutagenicity assays ignore whole animal protective mechanisms, may provide unphysiological metabolism, and may be either too sensitive (e.g., testing at orders-of-magnitude higher doses than can be ingested) or not sensitive enough (e.g., short-term treatments inadequately model chronic exposure in bioassay). Bacterial systems, particularly the Ames assay, cannot in principle detect chromosomal events which are involved in both carcinogenesis and germ line mutations in man. Some compounds induce only chromosomal events and little or no detectable single-gene events (e.g., acyclovir, caffeine, methapyrilene). In vivo mutagenicity assays are more physiological but appear to be relatively insensitive due to the inability to achieve sufficiently high acute plasma levels to mimic cumulative long-term effects. Examination of the mutagenicity of naturally occurring analogs may indicate the irrelevance of a test compound's mutagenicity (e.g., deoxyguanosine and the structurally related antiviral drug, acyclovir, have identical mutagenicity patterns). Life-threatening or severe debilitating diseases (e.g., cancer, severe psychoses, severe crippling arthritis, sight-threatening diseases) may justify treatment with mutagenic or even carcinogenic therapeutic agents (benefit/risk considerations).(ABSTRACT TRUNCATED AT 400 WORDS)     

An Alternative Approach to Assess Exchangeability of a Test Treatment and the Standard Treatment with Normally Distributed Response∗

In order to assess the equivalence of two treatments, clinical trials are designed to test against the null hypothesis that the difference (or ratio) of two means (proportions) is either smaller than a pre-specified lower equivalence limit or larger than a pre-specified upper equivalence limit. For example, in generic drug evaluation, such approach is defined as average bioequivalence. However, average equivalence type test is often criticized as lack of the ability to assess the exchangeability of the two treatments. In this article, we restate the statistical hypotheses in the form of stochastic inequalities. The stochastic statement can then be generalized to define the probability of exchangeability (i.e., coverage percentage) of the two treatments. The approach will be illustrated with a numeric example.     

An alternative approach to assess exchangeability of a test treatment and the standard treatment with normally distributed response

In order to assess the equivalence of two treatments, clinical trials are designed to test against the null hypothesis that the difference (or ratio) of two means (proportions) is either smaller than a pre-specified lower equivalence limit or larger than a pre-specified upper equivalence limit. For example, in generic drug evaluation, such approach is defined as average bioequivalence. However, average equivalence type test is often criticized as lack of the ability to assess the exchangeability of the two treatments. In this article, we restate the statistical hypotheses in the form of stochastic inequalities. The stochastic statement can then be generalized to define the probability of exchangeability (i.e., coverage percentage) of the two treatments. The approach will be illustrated with a numeric example.     

Treatment options for patients with hepatitis C: role of pharmacists in optimizing treatment response and managing adverse events

Chronic hepatitis C is associated with substantial morbidity and mortality and poses a considerable socioeconomic burden. Improved treatment regimens, including the standard of care pegylated interferon alfa and ribavirin, have increased sustained virologic response rates; however, treatment has a long duration and is often associated with adverse events that may affect adherence. The goal of therapy is viral eradication and reduced disease-related complications such as fibrosis, cirrhosis, and hepatocellular carcinoma. The clinical outcome of hepatitis C virus infection is altered with antiviral treatment, which can be influenced by host (e.g., weight, ethnicity, health) and viral (e.g., genotype, baseline viremia) factors. Overall, sustained virologic response was attained by 54-63% of patients in clinical trials treated with pegylated interferon alfa-2a or -2b and ribavirin. However, this benefit is not without risk. Interferon-induced adverse events include flu-like symptoms, bone marrow suppression, and emotional or cognitive effects, whereas hemolytic anemia accounts for most ribavirin dosage reductions. These adverse events may be ameliorated with dosage adjustments, symptom therapy, and judicious use of preventive strategies (e.g., antidepressants, hematopoietic growth factors). Appropriate management of adverse events can increase treatment adherence, thereby enhancing outcomes and improving quality of life. Pharmacists are in an ideal position to improve the treatment of patients with chronic hepatitis C by providing education about the disease and its treatments and associated adverse events and by emphasizing the importance of treatment adherence for successful outcomes.